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#Positional Encoding

Showing: 25 courses
Aladdin Persson

NeRFs- Neural Radiance Fields - Paper Explained

1 rewiews
Explore neural radiance fields for 3D scene representation and view synthesis, covering network architecture, key concepts, learning process, and advanced techniques.
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10 Lesons
20 minutes
On-Demand
Free-Video
Discover AI

Self-Extending LLM Context Windows Using Grouped Self-Attention

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Discover how to extend LLM context windows through grouped self-attention, enabling longer text processing without model retraining. Learn implementation techniques and practical applications.
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10 Lesons
26 minutes
On-Demand
Free-Video
Discover AI

How to Code Long-Context LLMs - LongLoRA Implementation with Llama 2 100K

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Dive into fine-tuning techniques for extending LLM context lengths using LongLoRA, featuring practical implementation on Llama 2 and Flash Attention 2 optimization for handling extensive sequences.
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15 Lesons
36 minutes
On-Demand
Free-Video
Data Science Courses

Deep Learning: Transformers and Encoder-Decoder Architecture - Lecture 10

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Dive into transformer architectures, exploring encoder-decoder mechanisms and positional embeddings for advanced deep learning applications.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
The Full Stack

Transfer Learning and Transformers - Full Stack Deep Learning - Spring 2021

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Explore transfer learning's evolution from computer vision to NLP, diving into embeddings, language models, and the revolutionary Transformer architecture. Gain insights into various models and their applications.
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9 Lesons
49 minutes
On-Demand
Free-Video
Valerio Velardo - The Sound of AI

Transformers Explained - Part 1: Generative Music AI

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Comprehensive exploration of transformer architectures in AI, covering intuition, theory, and mathematical formalization, with focus on their application in music and audio processing.
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25 Lesons
1 hour 13 minutes
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

Attention Is All You Need - Transformer Paper Explained

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Detailed walkthrough of the original transformer architecture, covering tokenization, embeddings, attention mechanisms, and decoding, with a focus on machine translation applications.
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10 Lesons
39 minutes
On-Demand
Free-Video
Yannic Kilcher

LambdaNetworks- Modeling Long-Range Interactions Without Attention

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Explore LambdaNetworks, a novel approach to modeling long-range interactions in AI without traditional attention mechanisms, offering improved efficiency and performance in computer vision tasks.
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8 Lesons
1 hour
On-Demand
Free-Video
Yannic Kilcher

NeRF - Representing Scenes as Neural Radiance Fields for View Synthesis

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Explore NeRF, a neural network-based approach for 3D scene representation and novel view synthesis, achieving photorealistic results from sparse input images through volumetric rendering.
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11 Lesons
34 minutes
On-Demand
Free-Video
Yannic Kilcher

Perceiver - General Perception with Iterative Attention

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Explore DeepMind's Perceiver model, a versatile architecture that processes diverse input modalities using iterative attention, solving the quadratic bottleneck problem in Transformers.
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8 Lesons
30 minutes
On-Demand
Free-Video
The Full Stack

LLM Foundations - LLM Bootcamp

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Explore foundational concepts of large language models, including machine learning basics, Transformer architecture, and notable LLMs. Gain insights into pretraining datasets and instruction tuning.
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19 Lesons
48 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Transformer Neural Networks, ChatGPT's Foundation, Clearly Explained

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Clear explanation of Transformer Neural Networks, the foundation of ChatGPT and modern AI. Covers key concepts like word embedding, self-attention, and encoder-decoder architecture.
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13 Lesons
36 minutes
On-Demand
Free-Video
Yannic Kilcher

Attention Is All You Need

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Explore the groundbreaking Transformer architecture, revolutionizing sequence transduction with attention mechanisms. Learn its superior performance in machine translation and generalization to other NLP tasks.
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11 Lesons
27 minutes
On-Demand
Free-Video
CodeEmporium

Deep Dive into the Transformer Encoder Architecture

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Detailed exploration of transformer encoder architecture, covering embeddings, positional encodings, self-attention mechanisms, and key components for effective natural language processing.
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16 Lesons
21 minutes
On-Demand
Free-Video
CodeEmporium

The Complete Guide to Transformer Neural Networks

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Comprehensive exploration of Transformer neural networks for language translation, covering architecture, key components, and practical implementation insights.
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14 Lesons
28 minutes
On-Demand
Free-Video
Envato Tuts+

Transformers: Introduction and Fundamentals - Day 1

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Explore the fundamentals of Transformers, a powerful deep learning architecture revolutionizing natural language processing and beyond.
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1 Lesons
44 minutes
On-Demand
Free-Video
Serrano.Academy

Transformer Models: Understanding Their Architecture and Functionality - Part 3

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Demystifying Transformer models with visuals and examples, covering key concepts like attention mechanism, tokenization, embeddings, and fine-tuning for various NLP tasks.
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13 Lesons
44 minutes
On-Demand
Free-Video
Valence Labs

Transformers Meet Directed Graphs - Exploring Direction-Aware Positional Encodings

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Explore direction-aware positional encodings for transformers on directed graphs, enhancing performance in code understanding and sorting network correctness testing.
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14 Lesons
1 hour 15 minutes
On-Demand
Free-Video
USENIX

Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention

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Innovative attention mechanism for efficient LLM serving in multi-turn conversations, reducing computation costs and improving performance through hierarchical KV caching and optimized cache management.
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1 Lesons
22 minutes
On-Demand
Free-Video
Unify

Attention with Linear Biases Explained

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Explore attention mechanisms with linear biases in transformer models, enabling efficient extrapolation to longer sequences without explicit positional embeddings.
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1 Lesons
39 minutes
On-Demand
Free-Video
Trelis Research

Transformers from Scratch - Part 2: Building and Training a Weather Prediction Model

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Dive deep into advanced transformer concepts, exploring encoder-decoder architectures, GPT-4o, and positional embeddings. Apply knowledge to weather prediction and analyze model performance.
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15 Lesons
57 minutes
On-Demand
Free-Video
MIT HAN Lab

Transformer and Large Language Models - Part I - Lecture 12

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Explore Transformer architecture and Large Language Models in this comprehensive MIT lecture, covering key concepts and recent advancements in AI.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
MIT HAN Lab

Transformer and Large Language Models - Part I - Lecture 12

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Explore Transformer architecture and Large Language Models in this comprehensive MIT lecture, covering key concepts and recent advancements in AI.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
MIT HAN Lab

Vision Transformer - Lecture 14

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Explore Vision Transformers in deep learning, covering architecture, training, and applications. Gain insights into this powerful model for computer vision tasks.
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1 Lesons
1 hour 14 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Encoder-Only Transformers: Understanding BERT and RAG Architecture

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Discover how encoder-only transformers power RAG, sentiment analysis, and classification through clear explanations of word embedding, positional encoding, and attention mechanisms.
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5 Lesons
19 minutes
On-Demand
Free-Video